Lindsey N. Long

CMIP5 Climate Model Analyses: Climate Extremes in the United States

This is the fourth in a series of four articles on historical and projected climate extremes in the United States. Here, we examine the results of historical and future climate model experiments from the phase 5 of the Coupled Model Intercomparison Project (CMIP5) based on work presented at the World Climate Research Programme (WCRP) Workshop on CMIP5 Climate Model Analyses held in March 2012. Our analyses assess the ability of CMIP5 models to capture observed trends, and we also evaluate the projected future changes in extreme events over the contiguous Unites States. Consistent with the previous articles, here we focus on model-simulated historical trends and projections for temperature extremes, heavy precipitation, large-scale drivers of precipitation variability and drought, and extratropical storms. Comparing new CMIP5 model results with earlier CMIP3 simulations shows that in general CMIP5 simulations give similar patterns and magnitudes of future temperature and precipitation extremes in the Unite...

North American Climate in CMIP5 Experiments. Part I: Evaluation of Historical Simulations of Continental and Regional Climatology*

AbstractThis is the first part of a three-part paper on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) that evaluates the historical simulations of continental and regional climatology with a focus on a core set of 17 models. The authors evaluate the models for a set of basic surface climate and hydrological variables and their extremes for the continent. This is supplemented by evaluations for selected regional climate processes relevant to North American climate, including cool season western Atlantic cyclones, the North American monsoon, the U.S. Great Plains low-level jet, and Arctic sea ice. In general, the multimodel ensemble mean represents the observed spatial patterns of basic climate and hydrological variables but with large variability across models and regions in the magnitude and sign of errors. No single model stands out as being particularly better or worse across all analyses, although some models consistently outperform the others for certain variab...

North American Climate in CMIP5 Experiments: Part III: Assessment of Twenty-First-Century Projections*

AbstractIn part III of a three-part study on North American climate in phase 5 of the Coupled Model Intercomparison Project (CMIP5) models, the authors examine projections of twenty-first-century climate in the representative concentration pathway 8.5 (RCP8.5) emission experiments. This paper summarizes and synthesizes results from several coordinated studies by the authors. Aspects of North American climate change that are examined include changes in continental-scale temperature and the hydrologic cycle, extremes events, and storm tracks, as well as regional manifestations of these climate variables. The authors also examine changes in the eastern North Pacific and North Atlantic tropical cyclone activity and North American intraseasonal to decadal variability, including changes in teleconnections to other regions of the globe. Projected changes are generally consistent with those previously published for CMIP3, although CMIP5 model projections differ importantly from those of CMIP3 in some aspects, inc...

Drought Indices Based on the Climate Forecast System Reanalysis and Ensemble NLDAS

Abstract Drought indices derived from the Climate Forecast System Reanalysis (CFSR) are compared with indices derived from the ensemble North American Land Data Assimilation System (NLDAS) and the North American Regional Reanalysis (NARR) over the United States. Uncertainties in soil moisture, runoff, and evapotranspiration (E) from three systems are assessed by comparing them with limited observations, including E from the AmeriFlux data, soil moisture from the Oklahoma Mesonet and the Illinois State Water Survey, and streamflow data from the U.S. Geological Survey (USGS). The CFSR has positive precipitation (P) biases over the western mountains, the Pacific Northwest, and the Ohio River valley in winter and spring. In summer, it has positive biases over the Southeast and large negative biases over the Great Plains. These errors limit the ability to use the standardized precipitation indices (SPIs) derived from the CFSR to measure the severity of meteorological droughts. To compare with the P analyses, t...

A Statistical Forecast Model for Atlantic Seasonal Hurricane Activity Based on the NCEP Dynamical Seasonal Forecast

Abstract A hybrid dynamical–statistical model is developed for predicting Atlantic seasonal hurricane activity. The model is built upon the empirical relationship between the observed interannual variability of hurricanes and the variability of sea surface temperatures (SSTs) and vertical wind shear in 26-yr (1981–2006) hindcasts from the National Centers for Environmental Prediction (NCEP) Climate Forecast System (CFS). The number of Atlantic hurricanes exhibits large year-to-year fluctuations and an upward trend over the 26 yr. The latter is characterized by an inactive period prior to 1995 and an active period afterward. The interannual variability of the Atlantic hurricanes significantly correlates with the CFS hindcasts for August–October (ASO) SSTs and vertical wind shear in the tropical Pacific and tropical North Atlantic where CFS also displays skillful forecasts for the two variables. In contrast, the hurricane trend shows less of a correlation to the CFS-predicted SSTs and vertical wind shear in...

How Well Do Global Climate Models Simulate the Variability of Atlantic Tropical Cyclones Associated with ENSO

The variability of Atlantic tropical cyclones (TCs) associated with El Nino‐Southern Oscillation (ENSO) in model simulations is assessed and compared with observations. The model experiments are 28-yr simulations forced with the observed sea surface temperature from 1982 to 2009. The simulations were coordinated by the U.S. Climate Variability and Predictability Research Program (CLIVAR) Hurricane Working Group and conducted with five global climate models (GCMs) with a total of 16 ensemble members. The model performance is evaluated based on both individual model ensemble means and multimodel ensemble mean. The latter has the highest anomaly correlation (0.86) for the interannual variability of TCs. Previous observational studiesshowastrongassociationbetweenENSOandAtlanticTCactivity,aswellasdistinctionsduringeastern Pacific (EP) and central Pacific (CP) El Nino events. The analysis of track density and TC origin indicates that each model has different mean biases. Overall, the GCMs simulate the variability of Atlantic TCs well with weaker activity during EP El Nino and stronger activity during La Nina. For CP El Nino, there is a slight increase in the number of TCs as compared with EP El Nino. However, the spatial distribution of track density and TC origin is less consistent among the models. Particularly, there is no indication of increasing TC activity overtheU.S.southeast coastalregionduringCPElNinoasinobservations.Thedifferencebetweenthemodels andobservationsislikelyduetothebiasofthemodelsinresponsetotheshiftoftropicalheatingassociatedwith CP El Nino, as well as the model bias in the mean circulation.

An Assessment of Multimodel Simulations for the Variability of Western North Pacific Tropical Cyclones and Its Association with ENSO

AbstractAn assessment of simulations of the interannual variability of tropical cyclones (TCs) over the western North Pacific (WNP) and its association with El Nino–Southern Oscillation (ENSO), as well as a subsequent diagnosis for possible causes of model biases generated from simulated large-scale climate conditions, are documented in the paper. The model experiments are carried out by the Hurricane Work Group under the U.S. Climate Variability and Predictability Research Program (CLIVAR) using five global climate models (GCMs) with a total of 16 ensemble members forced by the observed sea surface temperature and spanning the 28-yr period from 1982 to 2009. The results show GISS and GFDL model ensemble means best simulate the interannual variability of TCs, and the multimodel ensemble mean (MME) follows. Also, the MME has the closest climate mean annual number of WNP TCs and the smallest root-mean-square error to the observation.Most GCMs can simulate the interannual variability of WNP TCs well, with st...

Characteristics of Drought and Persistent Wet Spells over the United States in the Atmosphere–Land–Ocean Coupled Model Experiments

AbstractAtmosphere–land–ocean coupled model simulations are examined to diagnose the ability of models to simulate drought and persistent wet spells over the United States. A total of seven models are selected for this study. They are three versions of the NCEP Climate Forecast System (CFS) coupled general circulation model (CGCM) with a T382, T126, and T62 horizontal resolution; GFDL Climate Model version 2.0 (CM2.0); GFDL CM2.1; Max Planck Institute (MPI) ECHAM5; and third climate configuration of the Met Office Unified Model (HadCM3) simulations from the World Climate Research Programme (WCRP) Coupled Model Intercomparison Project phase 3 (CMIP3) experiments.Over the United States, drought and persistent wet spells are more likely to occur over the western interior region, while extreme events are less likely to persist over the eastern United States and the West Coast. For meteorological drought, which is defined by precipitation (P) deficit, the east–west contrast is well simulated by the CFS T382 an...

Atlantic Tropical Cyclone Activity in Response to the MJO in NOAA’s CFS Model

AbstractThe Madden–Julian oscillation (MJO) is known to exert some control on the variations of North Atlantic tropical cyclone (TC) activity within a hurricane season. To explore the possibility of better TC predictions based on improved MJO forecasts, retrospective hindcast data on MJO and on TC activity are examined both in the current operational version of the CFSv2 model (T126 horizontal resolution) and a high-resolution (T382) experimental version of CFS. Goals are to determine how well each CFS version reproduces reality in 1) predicting MJO and 2) reproducing observed relationships between MJO phase and TC activity. For the operational CFSv2, skill of forecasts of TC activity is evaluated directly.Both CFS versions reproduce MJO behavior realistically and also roughly approximate observed relationships between MJO phase and TC activity. Specific biases in the high-resolution CFS are identified and their causes explored. The high-resolution CFS partially reproduces an observed weak tendency for TC...